Abstract
Acoustic vibration signal analysis and coal bunker level recognition system in ball mill is used as a tool of acoustic vibration signal analysis system to extract characteristic variable to control the coal bunker level. With this system, the ball mill can operate in a safely condition, and work efficiency can be improved. In this paper, the development of acoustic vibration signal analysis, coal bunker level recognition system, and the result of test in practice are introduced. Hilbert transform and the working principle of the ball mill is analyzed. By the envelope of acoustic vibration signal is extracted. The most important part of the paper is the envelope analysis of acoustic vibration signal. Using wavelet transform we Extract characteristic vector and Using BP neural network is made by the mapping between the characteristic and the coal bunker level actualize the coal bunker level recognition.
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